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Coherent integration and detection algorithm for hypersonic target based on modified pulse compression and Keystone transform

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ELECTRONICS LETTERS 2021年第25期57卷 989-991页

作者： Yu, Wenchao Lu, Xingyu Su, Weimin Gu, Hong Yang, Jianchao Nanjing Univ Sci & Technol Sch Elect & Opt Engn Nanjing Peoples R China

This letter considers the coherent integration and detection for hypersonic target in the first-order approximate (FOA) echo model. The proposed algorithm first accomplishes the modified pulse compression utilising the designed reference signal, then conducts the Keystone transform (KT) based coherent integration method to detect the target. Compared with the existing methods which model the received signal without considering the target's intrapulse motion, the proposed method has a lower modeling error and can maintain good noise robustness for weak hypersonic target detection. Experimental results are given to show the effectiveness of the proposed method.

关键词： modified pulse compression utilising radar imaging detection algorithm approximation theory first-order approximate coherent integration method target tracking radar tracking lower modeling error object detection designed reference signal Doppler radar weak hypersonic target detection radar detection received signal Keystone transform radar signal processing

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Video adaptive watermark embedding and detection algorithm based on phase function equation

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APPLIED MATHEMATICS AND NONLINEAR SCIENCES 2022年第1期8卷 1445-1454页

作者： Chao, Yan Wang, Hao Liu, Shuying Shorman, Samer Fuyang Normal Univ Sch Comp & Informat Engn Fuyang 236037 Anhui Peoples R China Appl Sci Univ Coll Arts & Sci Eker Bahrain

In order to improve the video watermark embedding strength and balance the transparency of the watermark system, this paper proposes a combination of all phase Biorthogonal Transform and watermark embedding to complete the experiment. Firstly, the all phase biorthogonal transform is described. Referring to the construction process of APBT, combined with APDF and DST, a new all phase biorthogonal transform, all phase discrete sinusoidal biorthogonal transform (APDSBT), is proposed. This paper makes full use of MPEG-2 compression format to embed watermark directly in DCT domain. The low-frequency coefficients in the DCT block of the brightness space of I frame are selected as the watermark embedding space. The brightness component of each image block is transformed by two-dimensional DCT in the unit of 8x8 image blocks. By introducing the idea of energy receiver into the detection of digital watermark, the following correlation detector can be obtained. Implemented with MATIAB and VC + +. In the experiment, the foreman video test sequence is used as the watermark carrier, and the copyright logo image designed by ourselves is used as the watermark image to test the video watermarking system. The results show that when the coding rate is 3Mvps, the accuracy of each plane is 100%, 98.48%, 98.12% and 96.27% respectively. When the coding rate is 2.6Mvps, the accuracy of each plane is 100%, 96.38%, 94.87% and 95.21% respectively. This algorithm selects the frame of video to embed watermark. On the premise of ensuring video quality, this algorithm is robust to common video watermark attacks (MPEG compression, frame loss, frame clipping and frame rearrangement).

关键词： Phase function Video Watermark embedding detection algorithm Coding rate

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An iPhone application using a novel stool color detection algorithm for biliary atresia screening

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PEDIATRIC SURGERY INTERNATIONAL 2017年第10期33卷 1115-1121页

作者： Hoshino, Eri Hayashi, Kuniyoshi Suzuki, Mitsuyoshi Obatake, Masayuki Urayama, Kevin Y. Nakano, Satoshi Taura, Yasuyuki Nio, Masaki Takahashi, Osamu St Lukes Int Univ Ctr Clin Epidemiol Ctr Clin Acad Chuo Ku 5th FloorTsukiji 3-6-2 Tokyo 1040045 Japan Juntendo Univ Grad Sch Med Dept Pediat Tokyo Japan Kochi Med Sch Dept Pediat Surg Nankoku Kochi Japan Natl Ctr Child Hlth & Dev Dept Social Med Tokyo Japan Nagasaki Univ Sch Biomed Sci Dept Surg Oncol Nagasaki Japan Tohoku Univ Sch Med Dept Pediat Surg Sendai Miyagi Japan

The stool color card has been the primary tool for identifying acholic stools in infants with biliary atresia (BA), in several countries. However, BA stools are not always acholic, as obliteration of the bile duct occurs gradually. This study aims to introduce Baby Poop (Baby unchi in Japanese), a free iPhone application, employing a detection algorithm to capture subtle differences in colors, even with non-acholic BA stools. The application is designed for use by caregivers of infants aged approximately 2 weeks-1 month. Baseline analysis to determine optimal color parameters predicting BA stools was performed using logistic regression (n = 50). Pattern recognition and machine learning processes were performed using 30 BA and 34 non-BA images. Additional 5 BA and 35 non-BA pictures were used to test accuracy. Hue, saturation, and value (HSV) were the preferred parameter for BA stool identification. A sensitivity and specificity were 100% (95% confidence interval 0.48-1.00 and 0.90-1.00, respectively) even among a collection of visually non-acholic, i.e., pigmented BA stools and relatively pale-colored non-BA stools. Results suggest that an iPhone mobile application integrated with a detection algorithm is an effective and convenient modality for early detection of BA, and potentially for other related diseases.

关键词： Biliary atresia Screening Stool color iPhone application detection algorithm

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Background clutter and detection algorithm-based staring IR seeker performance evaluation

Background clutter and detection algorithm-based staring IR ...

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Conference on Infrared Components and Their Applications

作者： Chang, HH Zhang, JQ Wang, XR Li, Y Xidian Univ Sch Tech Phys Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)0819455954

Detecting a target out of its surrounding background is a major problem in various infrared seekers. The cluttered scenarios present extreme challenges for the modern IR seekers and are the focus of technology efforts. So, a complete performance evaluation model should include all of the following elements: i) the background ii) the target, iii) the atmosphere, iv) the sensor, and v) the image processing algorithms. Since the staring IR seeker systems are emerging as the latest application of the thermal infrared technology, it suffers the most from the lack of complete performance evaluation models. We present a robust performance evaluation technique for staring IR seekers based on signal-to-interference ratio (SIR), with the quantitative description of the background clutter and detection algorithms emphasized. The power transfer functions of the optical system detector and electronic are established to describe energy transmission of the signal and interference (noise and clutter) through the IR seeker, and the targets' radiant intensity statistics as well as the noise's statistical characteristics are also taken into account. In order to quantify the background clutter, we use a clutter measure based on its energy content power spectral density (PSD). Based on this measure, a SIR is developed to analyze detection performance. Furthermore, the influence of several classical detection algorithms on the SIR is analyzed.

关键词： staring IRFPA background clutter signal-to-interference ratio wavelet detection algorithm

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Unsupervised detection algorithm of Concrete Bridge Cracks in Complex Environment Based On Digital Image 2

Unsupervised Detection Algorithm of Concrete Bridge Cracks i...

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2nd International Conference on Big Data and Artificial Intelligence and Software Engineering (ICBASE)

作者： Sun, Shiyuan Hubei Prov Transportat Planning & Design Inst Co Wuhan 430051 Hubei Peoples R China

ISBN: (纸本)9781665427098

The existing detection algorithms have the problem of fuzzy characteristics of concrete bridge cracks, resulting in long main body iteration time. An unsupervised detection algorithm of concrete bridge cracks in complex environment based on digital image is designed. The spatial domain image is collected and transformed into a new gray value according to the mapping relationship. The digital image identifies the complex environment type, refines the crack edge in the image, obtains the crack characteristics of concrete bridges, measures the extension degree of cracks, and uses the principal component analysis method to set an unsupervised detection model. Experimental results: the designed unsupervised detection algorithm for concrete bridge cracks in complex environment and the main iterative time mean of the other two detection algorithms are 51.619s, 72.790s and 75.044s, which proves that the detection algorithm integrating digital image technology has higher performance.

关键词： digital image complex environment cracks in concrete bridges unsupervised detection algorithm main body iteration time

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Research on Human Stoop Activity Energy Expenditure detection algorithm Based on AHRS Transducer 16

Research on Human Stoop Activity Energy Expenditure Detectio...

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16th IEEE International Conference on Mechatronics and Automation (IEEE ICMA)

作者： Wang, Wei Wei, Wei Qu, Zhicheng Cheng, Lidan Gu, Jihua Lin, Xichuan Soochow Univ Dept Detect Technol & Automat Device Suzhou Jiangsu Peoples R China

ISBN: (纸本)9781728116976

The effectiveness of the measurement method of human exercise energy consumption based on accelerometer has been confirmed by research institutes in recent years. Aiming at the shortcomings of the accuracy of existing algorithms for human calorie consumption, this article aims at the importance of the detection of stoop activity energy expenditure (SAEE), a new system of detection SAEE based on AHRS transducer was presented. With collecting and analyzing data, a method for calculating the motion parameters and a new algorithm of detection SAEE was developed. The experimental results prove that the algorithm can accurately estimate bending energy consumption, and the accuracy can reach 84%. It has certain reference value for bending energy consumption calculation.

关键词： energy expenditure AHRS forward bending detection algorithm

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An Improved Complex Network Community detection algorithm Based on K-Means

An Improved Complex Network Community Detection Algorithm Ba...

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Conference on the Future Computer and Control Systems

作者： Wang, Yuqin Jilin Business & Technol Coll Dept Informat Engn Changchun 130062 Peoples R China

ISBN: (纸本)9783642293894

In order to find community structure that exists in complex network structure, this paper introduced K-means approach to the complex network community structure of the research. This paper studies the complex network of community structure detection algorithm, through the existing algorithm learn and study, proposed an improved algorithm based on K-means. Not know the premise of community structure for the complex networks division, the algorithm is simple and easy to understand, and the algorithm was used in karate network, through experimental verification, experimental results show that the algorithm is effective.

关键词： complex networks community structure k-means detection algorithm algorithm analysis

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A detection algorithm for faint sources based on 1-d projection for a lobster-eye X-ray imaging system

A detection algorithm for faint sources based on 1-d project...

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Conference on Space Telescopes and Instrumentation - Ultraviolet to Gamma Ray / SPIE Astronomical Telescopes + Instrumentation Conference

作者： Sawano, Tatsuya Yonetoku, Daisuke Arimoto, Makoto Li, Jin Mihara, Tatehiro Ogino, Naoki Sakamoto, Takanori Serino, Motoko Kanazawa Univ Adv Res Ctr Space Sci & Technol Inst Sci & Engn Kanazawa Ishikawa 9201192 Japan Kanazawa Univ Coll Sci & Engn Sch Math & Phys Kanazawa Ishikawa 9201192 Japan Aoyama Gakuin Univ Dept Phys & Math Chuo Ku 5-10-1 Fuchinobe Sagamihara Kanagawa 2525258 Japan RIKEN MAXI Team Inst Phys & Chem Res 2-1 Hirosawa Wako Saitama 3510198 Japan

ISBN: (纸本)9781510636767

We propose an optimized source detection algorithm with an X-ray wide-field imaging detector based on lobster-eye (LE) optics to realize better sensitivity. In our method, we take two parts of region of interest (ROI) in which we test the number of X-ray events exceed a certain threshold level. Since we compose the condition that the excesses of the photons are required for the both parts of the ROI, we can lower the detection threshold level with a less false alert rate. We take two comparative methods in which the ROI consists of one part, and compared the performance of them. We formulated an appropriate threshold level and sensitivity for two comparable detection methods as well as our proposed method. We found that the detection sensitivity of our method is improved by a factor of about 30% at most than that of the comparable methods in the nominal case of the proposed HiZ-GUNDAM mission. We also found that which detection method has better sensitivity depends on the background event rate. We checked that the formulation works well by comparing to a Monte Carlo simulation in the case of the HiZ-GUNDAM condition. The formula can be applied to any future missions with LE optics to design which detection algorithm is suitable for optimizing sensitivity.

关键词： lobster-eye optics X-ray all-sky monitoring gamma-ray bursts detection algorithm

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Study of Measurement and detection algorithm of LVDC Residual Current 66

Study of Measurement and Detection Algorithm of LVDC Residua...

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66th IEEE Holm Conference on Electrical Contacts and Intensive Course (HLM)

作者： Xie, Zhimin Li, Xingwen Wang, Jing Chen, Silei Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian Peoples R China Shenzhen Power Supply Bur Shenzhen Peoples R China Xian Univ Technol Sch Elect Engn Xian Peoples R China

ISBN: (纸本)9781665422208

With the rapid development of dc system, the residual current in dc system has become an urgent problem to be solved. However, the type B residual current devices (RCD) for ac systems could not be directly used in dc systems. The ac residual current caused by distributed capacitance and the rectifier seriously interferes with the accurate detection of the dc residual current. A detection simulation model of dc residual current based on magnetic modulation was established. The authors also proposed detection algorithms based on Kalman filter and moving average filter separately. The experimental results showed that the proposed model and detection algorithms were effective. They could detect the residual current in the dc system under ac interferences.

关键词： dc residual current LVDC detection algorithm magnetic modulation model

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Deep Neural Network Based detection algorithm for High-Order Modulation in Uplink Massive MIMO 17

Deep Neural Network Based Detection Algorithm for High-Order...

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17th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC)

作者： Hou, Huijun Li, Lin Meng, Weixiao CETC Res Inst 14 Nanjing Peoples R China Nanjing Univ Posts & Telecommun Jiangsu Key Lab Broadband Wireless Commun & Inten Nanjing Peoples R China Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing Peoples R China Harbin Inst Technol Commun Res Ctr Harbin Peoples R China

ISBN: (纸本)9781728186160

For the 6th generation (6G) communications, the interference exploitation generated from a growing number of intelligent factors with ultra scale is great challenge for the low complexity detection algorithms in the uplink multiuser massive multiple input and multiple output (MIMO) systems, especially for detecting high order quadrature amplitude modulation (QAM) signals. The deep learning technology is one of the key technical solutions for 6G. In this paper, a deep neural network based semidefinite relaxation (DNNSR) detection algorithm is proposed on the basis of the graphical detection model for uplink multiuser massive MIMO systems. Compared with the counterpart detection algorithms, along with a low polynomial average per symbol computational complexity, the proposed DNNSR detection algorithm requires lower average received signal to noise ratios to obtain better bit error rate performance as well as achieve theoretical spectral efficiency for graphical high order QAM signals in the uplink multiuser massive MIMO systems.

关键词： massive MIMO deep neural network detection algorithm high order modulation computational complexity

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